A novel peak signal feature segmentation process for epileptic seizure detection

摘要: Epilepsy is a brain disease in nerves which causes sudden seizure, sensations, and once while loss of mindfulness. This disorder difficult to find manually because its unpredictable nature since it very hard treat. The World Health Organization states that fifty million people having this type worldwide. Automatic detection assumes significant role the finding epilepsy for can get imperceptible data Epileptic Electroencephalogram Signals precisely diminish burdens medical field. Brain’s function monitored by using these EEG signals electrically. goal paper classification on (EEG) Bonn University datasets. In order address challenge, we propose new Peak Signal Features (PSF) method extracts high low peak features from signals. addition, Support Vector Machine, Decision Tree K-Nearest Neighbor are used classification. Finally, overall accuracy Mean Square Error rates above three methods with proposed measured. experimental result demonstrates effectiveness approach. It also proves SVM gives better than other methods.